Cloud Cost Calculator

How Much Will Your Cloud Infrastructure Cost?

Cloud pricing is notoriously complex. AWS alone offers over 200 services, each with its own pricing model, tiers, and regional variations. A single misconfiguration — choosing on-demand instead of reserved instances, or underestimating data transfer — can double or triple your monthly bill. Our calculator simplifies this by focusing on the three core cost drivers that account for 70–90% of most cloud bills: compute (servers/VMs), storage, and data transfer (bandwidth).

Enter your expected compute requirements (CPU, RAM, hours of usage), storage needs (type and capacity), and estimated data egress. The calculator produces monthly cost estimates across AWS, Azure, and Google Cloud so you can compare providers for your specific workload.

Quick estimates: A basic web application (2 vCPU, 4GB RAM, 50GB SSD, 500GB egress): $50–100/month. A mid-scale SaaS platform (8 vCPU, 32GB RAM, 500GB storage, managed database, 2TB egress): $400–800/month. Enterprise workloads with GPU compute, multi-region deployment, and high availability: $5,000–50,000+/month.

The Three Pillars of Cloud Cost

Compute is typically the largest cost category — the virtual machines (EC2 on AWS, Compute Engine on GCP, Virtual Machines on Azure) that run your applications. Cost depends on instance type (CPU count, RAM, GPU), pricing model (on-demand, reserved, spot), region, and operating system.

On-demand instances are billed by the second or hour with no commitment. They're the most flexible but most expensive option. A general-purpose instance with 4 vCPU and 16GB RAM costs approximately $0.17–0.20/hour on-demand across major providers — roughly $125–150/month if running 24/7.

Reserved instances (1 or 3-year commitment) reduce compute costs by 30–60% compared to on-demand. If you know you'll need consistent compute for 12+ months, reserved pricing is almost always the right choice. A 3-year reserved instance can cost 60% less than on-demand.

Spot instances (AWS) / preemptible VMs (GCP) / spot VMs (Azure) use excess provider capacity at 60–90% discounts. The catch: they can be interrupted with 30 seconds to 2 minutes notice when the provider needs that capacity. Ideal for batch processing, data analysis, CI/CD pipelines, and any workload tolerant of interruption. Not suitable for production web servers or databases.

Storage costs depend on the type of storage, the amount, and how frequently you access it. Standard SSD (gp3 on AWS, Balanced Persistent Disk on GCP) costs $0.08–0.10/GB/month — 100GB costs roughly $8–10/month. HDD-based storage runs $0.04–0.05/GB/month. Archive/cold storage (S3 Glacier, GCS Coldline) costs $0.004–0.01/GB/month — incredibly cheap for long-term storage but with retrieval fees that can be substantial if you access data frequently.

Object storage (S3, GCS, Azure Blob) is the most common storage type for web applications — it stores files, images, backups, and logs at very low cost. Don't forget request costs: each PUT, GET, LIST, and DELETE operation has a small per-request charge (typically $0.0004–0.005 per 1,000 requests) that can add up with high-frequency access patterns.

Data transfer (egress) is the cost most commonly underestimated — and it's where cloud providers make significant margin. Ingress (data coming into the cloud) is free across all major providers. Egress (data leaving the cloud to the internet) costs $0.08–0.12/GB after the first 100GB/month on AWS and Azure, and $0.08–0.12/GB on GCP after the first 200GB.

For a content-heavy website serving 10TB of egress per month, data transfer alone costs $800–1,200/month. This is why CDNs (Content Delivery Networks) like Cloudflare, CloudFront, or Fastly are essential — they cache content at edge locations closer to users, reducing egress from your origin server by 60–90%.

Provider Comparison: AWS vs Azure vs GCP

AWS (Amazon Web Services) has the largest market share (~31%) and broadest service catalog. It's the safe default choice with the most documentation, community support, and third-party integrations. Pricing is competitive but rarely the cheapest for any specific service. AWS excels at enterprise workloads, has the most regions globally, and offers the deepest ecosystem.

Azure (Microsoft Azure) holds approximately 24% market share and integrates seamlessly with Microsoft's enterprise ecosystem (Active Directory, Office 365, Windows Server, SQL Server). Organizations already using Microsoft tools often find Azure the most natural fit. Azure's pricing is comparable to AWS, with occasional advantages on Windows-based workloads due to licensing benefits.

GCP (Google Cloud Platform) holds approximately 11% market share but leads in data analytics (BigQuery), machine learning (Vertex AI), and Kubernetes (GKE — Google invented Kubernetes). GCP's "sustained use discounts" automatically reduce prices for instances running more than 25% of a month — no commitment required, unlike AWS/Azure reserved pricing. This makes GCP attractive for workloads with variable but generally consistent usage.

For startups and small projects: GCP often wins on simplicity and automatic discounts. DigitalOcean, Hetzner, and Vultr offer significantly cheaper VPS hosting ($5–50/month) for simple applications that don't need the full cloud ecosystem. Vercel and Netlify handle frontend deployment for free or near-free for most projects.

For enterprise: AWS and Azure dominate due to compliance certifications, enterprise support, hybrid cloud capabilities, and established procurement relationships. The choice often comes down to existing Microsoft vs Amazon ecosystem alignment.

Hidden Costs to Watch For

Data transfer between services within the same provider but different availability zones costs $0.01–0.02/GB. Between regions, it's even more. Multi-AZ deployments for high availability can accumulate surprising inter-zone transfer costs.

Managed database services (RDS, Cloud SQL, Cosmos DB) cost 2–5x more than running the same database on a self-managed VM. The convenience of automated backups, patching, and scaling is worth it for most teams, but the premium is substantial. A managed PostgreSQL instance with 4 vCPU and 16GB RAM costs $300–500/month — roughly 3x the cost of the underlying compute alone.

Load balancers charge both a fixed hourly fee ($0.02–0.03/hour ≈ $15–22/month) and a per-GB data processed fee. For high-traffic applications, load balancer costs can reach $100+/month.

NAT Gateways (AWS) charge $0.045/hour ($32/month) plus $0.045/GB processed. A private subnet with moderate outbound traffic can easily see $100–200/month in NAT Gateway charges alone. This is one of the most common "bill shock" items for AWS users.

Logging and monitoring services charge by data volume. CloudWatch, Cloud Logging, and Azure Monitor can cost $50–500/month depending on log volume. Setting appropriate log retention policies and filtering unnecessary logs prevents runaway monitoring costs.

Cost Optimization Strategies

Right-size your instances. Most cloud instances are over-provisioned — running on larger VMs than the workload requires. Use provider tools (AWS Compute Optimizer, GCP Recommender, Azure Advisor) to identify underutilized instances. Downsizing from a 4-vCPU instance to a 2-vCPU instance when average CPU usage is 15% cuts compute cost in half with no performance impact.

Use reserved/committed pricing for steady workloads. If an instance runs 24/7, reserved pricing saves 30–60%. Compute 3-year savings plans on AWS offer the deepest discounts. GCP's sustained use discounts apply automatically without any commitment.

Leverage spot/preemptible instances. For batch processing, CI/CD, rendering, data analysis, and machine learning training, spot instances save 60–90%. Architecture your application to handle interruptions (checkpointing, auto-restart) and spot becomes your cheapest compute option.

Implement auto-scaling. Scale compute up during peak hours and down during off-hours. A web application that scales from 2 instances at night to 8 during business hours uses 60% less compute than running 8 instances 24/7.

Use a CDN aggressively. Cloudflare's free tier provides unlimited bandwidth for cached content — shifting egress from expensive cloud bandwidth to free CDN delivery. For content-heavy sites, a CDN alone can reduce cloud costs by 30–50%.

Delete unused resources. Unattached EBS volumes, idle load balancers, stale snapshots, and orphaned IP addresses silently accumulate charges. Run monthly cleanup audits. Use tools like AWS Cost Explorer, GCP Billing Reports, or third-party tools like Infracost and Vantage.

Storage lifecycle policies. Automatically move infrequently accessed data to cheaper storage tiers. A policy that transitions objects to Glacier after 90 days and deletes after 365 days can reduce storage costs by 70–80% for log and backup data.